1. Field of the Invention
This invention relates to networks of sensors and actuators. More specifically, the invention is a method of employing a communal network of sensors and actuators to achieve a global objective based on localized decisions.
2. Description of the Related Art
Networks of sensors, actuators, and computers have been employed in numerous applications for several decades. For example, automobiles and aircraft contain sensor networks to monitor system health and manage performance. Mass transit systems augment human control with sensor networks that constantly monitor the location and speed of all traffic to ensure safety and efficiency. Sensor networks are extensively used to control environments and provide intrusion detection for buildings and complexes. Sensor networks are also used to control complex industrial processes to enhance efficiency of the manufacturing process, as well as to prevent disasters. Because of cost, size, and other constraints, these networks have typically been restricted to relatively small numbers of components. The conventional architecture of these networks positions a computer at some central location to collect sensor data, process that data, and issue commands to control some process response.
The advent of Micro-Electrical-Mechanical Systems (MEMS) technology in the last decade has made it possible to build inexpensive, small, self-powered devices containing a sensor, a computer, and wireless communication capability. These devices are sometimes referred to as “motes” to emphasize their small size or “nodes” to emphasize their role in a sensor network. It is expected that massive numbers of these small devices will be deployed in Wireless Sensor Networks (WSN) that can change the way we live and work by monitoring and modifying the environment.
Current WSN approaches concentrate on establishing networks for collection of sensor information and then routing that information to a centralized processor. That is, current sensor networks operate on a “sense and send” philosophy. These “sense and send” implementations rely on a central computer that must handle/process large amounts of data from the “global” (i.e., entire) set of sensors in the network. Thus, processing capability and cost are major constraints limiting the number of sensors that may be deployed using the “sense and send” philosophy. Accordingly, there are many applications where the “sense and send” philosophy is just not practical. One such application is aircraft noise attenuation.
Anyone who has stood near a modern aircraft is aware of the noise produced by the engines. Engine noise levels are not constant as they increase dramatically during takeoff and landing. This has led to potentially dangerous noise-abatement flight paths with steep turns and rapid altitude changes that are frequently required to minimize the noise for communities surrounding an airport. Some airports charge airlines based on quantity of noise “pollution” created by their aircraft. Thus, it is desirable to attenuate the noise by maximizing absorption under changing conditions.
One approach to noise abatement in an aircraft engine (e.g., a turbofan engine) is the application of acoustic treatment within the inner walls of the engine's nacelle. As sound propagates through the nacelle, noise is reduced or attenuated by the liner. The amount of attenuation is determined by design characteristics of the liner. Designing liners for optimal noise attenuation is complicated by the following factors:
(i) The aeroacoustic environment changes throughout the flight regime with non-negligible variations in frequency content.
(ii) The theoretical parameters specified in the design may not be met in the construction of the liner material.
(iii) Physical changes over time in the nacelle or the liner (e.g., contamination) change the noise absorption properties. Unfortunately, the multi-layer static liners that are currently used to address these factors add excess weight to the aircraft.